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dc.date.accessioned2020-05-25T19:24:48Z
dc.date.available2020-05-25T19:24:48Z
dc.date.created2019-04-26T09:46:25Z
dc.date.issued2019
dc.identifier.citationHoff, Rune Putter, Hein Mehlum, Ingrid Sivesind Gran, Jon Michael . Landmark estimation of transition probabilities in non-Markov multi-state models with covariates. Lifetime Data Analysis. 2019, 25(4), 660-680
dc.identifier.urihttp://hdl.handle.net/10852/76256
dc.description.abstractIn non-Markov multi-state models, the traditional Aalen–Johansen (AJ) estimator for state transition probabilities is generally not valid. An alternative, suggested by Putter and Spitioni, is to analyse a subsample of the full data, consisting of the individuals present in a specific state at a given landmark time-point. The AJ estimator of occupation probabilities is then applied to the landmark subsample. Exploiting the result by Datta and Satten, that the AJ estimator is consistent for state occupation probabilities even in non-Markov models given that censoring is independent of state occupancy and times of transition between states, the landmark Aalen–Johansen (LMAJ) estimator provides consistent estimates of transition probabilities. So far, this approach has only been studied for non-parametric estimation without covariates. In this paper, we show how semi-parametric regression models and inverse probability weights can be used in combination with the LMAJ estimator to perform covariate adjusted analyses. The methods are illustrated by a simulation study and an application to population-wide registry data on work, education and health-related absence in Norway. Results using the traditional AJ estimator and the LMAJ estimator are compared, and show large differences in estimated transition probabilities for highly non-Markov multi-state models.
dc.languageEN
dc.titleLandmark estimation of transition probabilities in non-Markov multi-state models with covariates
dc.typeJournal article
dc.creator.authorHoff, Rune
dc.creator.authorPutter, Hein
dc.creator.authorMehlum, Ingrid Sivesind
dc.creator.authorGran, Jon Michael
cristin.unitcode185,51,15,0
cristin.unitnameAvdeling for biostatistikk
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1
dc.identifier.cristin1694076
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Lifetime Data Analysis&rft.volume=25&rft.spage=660&rft.date=2019
dc.identifier.jtitleLifetime Data Analysis
dc.identifier.volume25
dc.identifier.issue4
dc.identifier.startpage660
dc.identifier.endpage680
dc.identifier.doihttps://doi.org/10.1007/s10985-019-09474-0
dc.identifier.urnURN:NBN:no-79326
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn1380-7870
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/76256/2/manuscript.pdf
dc.type.versionAcceptedVersion


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